Deep Learning for humans

NYU Course Notes & Resources

Collection of notebooks for time series analysis

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. Mo…

The official implemenataion of the "Denoising Architecture for Unsupervised Anomaly Detection in Time-Series" paper.

Advanced Python Mastery (course by @dabeaz)

PyTorch Tutorial for Deep Learning Researchers

Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

Materials of the Nordic Probabilistic AI School 2022.

Bayesian LSTM Implementation in PyTorch

Plain python implementations of basic machine learning algorithms

A Tensorflow / Keras implementation of "Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks" paper

An implementation of convolutional networks in NumPy!

list of papers, code, and other resources

This repository contains code for the paper: https://arxiv.org/abs/1905.03806. It also contains scripts to reproduce the results in the paper.

Explaining Git and GitHub.

Taxi fare prediction using tensorflow probability

Deep Learning Specialization by Andrew Ng on Coursera.

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

Comparisons of ARIMA , ANN and a Hybrid model for Timeseries forecasting

The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"